条纹投影用于不同景深物体的三维测量

Fringe projection profilometry for 3D measurement of objects with different depth of fields

  • 摘要: 条纹投影轮廓术(Fringe Projection Profilometry, FPP)由于其非接触、测量精度高等特点被广泛应用于缺陷检测、逆向工程、计算机视觉等领域中。然而,传统的FPP单次测量只能获得有限景深范围内的被测物体的三维轮廓,无法完成视场范围内不同景深的多个被测物体的同时精确测量。文中在传统FPP系统的基础上增加两面反射镜和两个三棱镜,搭建了一种镜面辅助的FPP系统。所提出的方法能将摄像机不同景深范围内的被测物体转换到同一景深范围内,从而实现不同景深的多个被测物体的三维轮廓高精度测量。实验通过6层标准石膏阶梯模型验证了景深对三维轮廓测量结果的影响;同时分别采用传统FPP和提出的FPP系统对不同景深范围内两个标准乒乓球同时进行了轮廓测量,传统FPP测得的摄像机聚焦点处和未聚焦的乒乓球的拟合半径相对误差分别为2.9%、34.3%,而镜面辅助的FPP测得的相对误差分别为2.7%、5.3%。结果表明:文中提出的方法能补偿由于景深引起的误差,从而验证了该方法在不同景深物体三维测量中的可行性。

     

    Abstract: Fringe projection profilometry (FPP) was widely used in defect detection, reverse engineering, computer vision and other fields due to its non-contact and high measurement accuracy. However, traditional FPP can only obtain the 3D profile of the measured object within limited depth of field in a single measurement, and can not achieve accurate measurement of multiple measured objects with different depth simultaneously. A mirror-assisted FPP system was constructed by adding two mirrors and two prisms on the basis of traditional FPP system in this paper. The proposed method can transform the measured objects in different depth of field ranges to the same depth of field range, so as to achieve high-precision measurement of the 3D profiles of multiple measured objects in different depth of field ranges. The effect of depth of field on 3D profile measurement results was verified using a standard six-step gypsum model. Meanwhile, the profiles of two standard table tennis within different depth of field ranges were measured using the traditional FPP system and the proposed FPP system. The table tennis radius as error results were obtained from the measured profile. The relative errors of the focused and the unfocused table tennis measured by the traditional FPP were 2.9% and 34.3%, respectively. And the corresponding measured errors by proposed mirror-assisted FPP were 2.7% and 5.3%, respectively. The results show that the proposed method can compensate the errors caused by the depth of field, and verifies the feasibility of the proposed method in 3D measurement with different depth of field ranges.

     

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